Machine Learning Operations Engineer

  • FORT BELVOIR, VA
  • Posted 3 days ago | Updated 10 hours ago

Overview

On Site
Full Time

Skills

Science
Continuous Integration and Development
Continuous Integration
Continuous Delivery
Scalability
Regulatory Compliance
JD
DevOps
Programming Languages
Python
Bash
Machine Learning Operations (ML Ops)
TensorFlow
Orchestration
Docker
Kubernetes
Cloud Computing
Amazon Web Services
Microsoft Azure
Google Cloud Platform
Google Cloud
Large Language Models (LLMs)
Natural Language Processing
Conflict Resolution
Problem Solving
Collaboration
Artificial Intelligence
Grafana
Workflow
Version Control
Machine Learning (ML)
Security Clearance
Information Technology
Systems Engineering
FOCUS

Job Details

Job ID: 2510599

Location: FORT BELVOIR, VA, US

Date Posted: 2025-10-07

Category: Engineering and Sciences

Subcategory: Machine Learning Engineer

Schedule: Full-time

Shift: Day Job

Travel: Yes, 10 % of the Time

Minimum Clearance Required: TS/SCI

Clearance Level Must Be Able to Obtain: TS/SCI with Poly

Potential for Remote Work: No

Description

SAIC is seeking a Machine Learning Operations Engineer to join our team in Fort Belvoir, Virginia.

The MLOps Engineer will be responsible for streamlining the deployment, monitoring, and maintenance of machine learning (ML) models and systems within the Army Intelligence & Security Enterprise (AISE). This role will focus on implementing MLOps practices to ensure scalability, reliability, and efficiency of AI/ML solutions in operational environments. The MLOps Engineer will collaborate with data scientists, ML engineers, and cloud engineers to deliver mission-critical AI capabilities.

Job Duties:
  • Design and implement MLOps pipelines to automate the deployment and monitoring of ML models.
  • Develop tools and frameworks to support continuous integration and continuous delivery (CI/CD) for AI/ML systems. Troubleshoot identified issues.
  • Collaborate with data scientists and ML engineers to optimize model performance and scalability.
  • Monitor deployed models for performance, drift, and reliability, and implement retraining workflows as needed.
  • Ensure compliance with security protocols and governance policies for AI/ML systems.
  • Stay updated on advancements in MLOps practices, tools, and technologies.
  • Support the operational integration of AI/ML solutions to enhance intelligence capabilities.

Qualifications

Required Education:
  • Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD or JD and zero (0) years or more experience; four (4) years of experience considered in lieu of degree.

Qualifications:
  • Five (5) or more years of experience in MLOps, DevOps, systems engineering, or related roles.
  • Proficiency in programming languages such as Python or Bash.
  • Strong understanding of MLOps tools and frameworks (e.g., MLflow, Kubeflow, TensorFlow Extended).
  • Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
  • Experience with cloud-based AI/ML platforms and tools (e.g., AWS, Azure, Google Cloud).
  • Experience with leveraging Large Language Models (LLMs) such as GPT, or similar frameworks for tasks like natural language processing (NLP), text generation, summarization, or conversational AI.
  • Excellent problem-solving and collaboration skills.

Desired Qualifications:
  • Advanced degree (Master's or PhD) in Machine Learning, Artificial Intelligence, or a related field.
  • Experience with monitoring tools for AI/ML systems (e.g., Prometheus, Grafana).
  • Familiarity with Army Intelligence Enterprise data requirements and workflows.
  • Knowledge of version control systems and practices for ML models and data.

Clearance:
  • Candidates must have an active TS/SCI with the ability to obtain a TS/SCI with Poly.



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